Proceedings ArticleDOI
Multi-agent technology for distributed data mining and classification
Vladimir Gorodetsky,O. Karsaeyv,Vladimir Samoilov +2 more
- pp 438-441
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TLDR
The paper presents the developed and implemented distributed data mining technology, architecture of the multi- agent software tool supporting this technology and demonstrates the key protocols used by agents in collaborative design of an applied multi-agent distributed datamining system.Abstract:
The core problem of multi-agent distributed data mining technology not concern particular data mining techniques although the latter is now paid the most attention. Its core problem concerns collaborative work of distributed software in design of multi-agent system destined for distributed data mining and classification. The paper presents the developed and implemented distributed data mining technology, architecture of the multi-agent software tool supporting this technology and demonstrates the key protocols used by agents in collaborative design of an applied multi-agent distributed data mining system.read more
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References
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TL;DR: This article summarizes four directions of machine-learning research, the improvement of classification accuracy by learning ensembles of classifiers, methods for scaling up supervised learning algorithms, reinforcement learning, and the learning of complex stochastic models.
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Issues in stacked generalization
Kai Ming Ting,Ian H. Witten +1 more
TL;DR: This paper addresses two crucial issues which have been considered to be a 'black art' in classification tasks ever since the introduction of stacked generalization: the type of generalizer that is suitable to derive the higher-level model, and the kind of attributes that should be used as its input.
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Combining Classifiers with Meta Decision Trees
Ljupčo Todorovski,Sašo Džeroski +1 more
TL;DR: The paper introduces meta decision trees (MDTs), a novel method for combining multiple classifiers that instead of giving a prediction, MDT leaves specify which classifier should be used to obtain a prediction.
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